EMG-based Estimation of Knee Torque and Angle using Recurrent Neural Network

抄録

This work presents a framework for the kinetics and kinematics estimation of the human knee joints in natural movements. In this study, we employed the long short-term memory (LSTM), a special recurrent neural network (RNN) architecture, as an estimation algorithm by using electromyography (EMG) features. The results suggest a potential application for online prediction of joint kinetics and kinematics without ground force measurements.